Name of the competition within which the project is being implemented: Competition for program-targeted funding for scientific and (or) scientific-technical programs for 2023-2025.
Project Supervisor: Darya L. Alontseva, Doctor of Sciences in Physics and Mathematics, Professor of Physics.
Identifiers:
- Scopus Research ID 6506822578 (https://www.scopus.com/authid/detail.uri?authorId=6506822578)
- ORCiD: 0000-0003-1472-0685 (https://orcid.org/0000-0003-1472-0685)
- Web of Science Researcher ID H-1535-2014 (https://www.webofscience.com/wos/author/record/151646)
- Mendeley (https://www.mendeley.com/reference-manager/library/all-references)
The research group of the project
№ | Full name | Project position | Identifiers (Scopus Author ID, Researcher ID, ORCID, if any) and links to related profiles | ||
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1 | Gennady K. Shadrin | Leading Researcher | Scopus Author ID https://www.scopus.com/authid/detail.uri?authorId=57170401000 ORCID https://orcid.org/0000-0002-4716-8383 |
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2
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Alexander L. Krasavin | Leading Researcher | Scopus Author ID https://www.scopus.com/authid/detail.uri?authorId=57189326266 | ||
3 | Alyona V. Russakova | Senior Researcher | Scopus Author ID https://www.scopus.com/authid/detail.uri?authorId=55669597600 Web of Science Researcher ID: O-8504-2017 https://www.webofscience.com/wos/author/record/1774379 |
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4 | Almira M. Zhilkashinova | Senior Researcher | Web of Science Researcher ID P-5882-2017 https://app.webofknowledge.com/author/record/27689909 Scopus Author ID 55890420000 https://www.scopus.com/authid/detail.uri?authorId=55890420000 ORCID 0000-0003-0948-2280 |
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Young scientists (up to 40 years old + trainees (Undergraduates, Master's students)) | |||||
№ | Full name | Project position | Identifiers (Scopus Author ID, Researcher ID, ORCID, if any) and links to related profiles | Note (teacher, student, undergraduate, doctoral student) | |
1 | Albina T. Kadyroldina | Senior Researcher | Scopus Author ID https://www.scopus.com/authid/detail.uri?authorId=57202922020 ORCID https://orcid.org/0000-0001-5572-4792 |
faculty | |
2 | Assel T. Kussaiyn-Murat | Senior Researcher | Scopus Author ID https://www.scopus.com/authid/detail.uri?authorId=57207456820 ORCID https://orcid.org/0000-0001-6867-6638 |
faculty | |
3 | Alexandr R. Khozhanov | Senior Researcher | Scopus Author ID https://www.scopus.com/authid/detail.uri?authorId=57220782525, ORCID https://orcid.org/0000-0002-3298-6359 |
doctoral student | |
4 | Arailym Zh. Orazova | Junior Researcher | ORCID https://orcid.org/0000-0002-3913-4562 | ||
5 | Maral B. Tolykbaeva | Junior Researcher | doctoral student | ||
6 | Gaukhar M. Nazenova | Junior Researcher | ORCID https://orcid.org/0000-0002-5415-094X | doctoral student | |
7 | Dmitriy A. Porubov | Engineer | faculty |
Project abstract:
Nowadays, the use of MEMS (microelectronic mechanical systems) technology is very promising for the control of mobile robots. MEMS inertia sensors are small, light, and cheap, provide fast measurements, and come with standard digital communications interfaces. However, the use of MEMS technologies for control tasks associated with solving the problem of establishing the spatial orientation of an object and reconstructing its trajectory is limited by the high noise level of inertia sensor data.
The main idea of the project is to integrate the mobile robot’s inertial navigation and the automatic control systems into one using machine learning methods and MEMS inertia sensor data as feedback signals for the robot control and navigation. Machine learning will be carried out using the data archives of the control system for different specified trajectories. The input data for learning will be calculated as the difference between the real and given trajectories of the mobile robot.
The main problem is the precise positioning and orientation for arbitrary types of robot movement and the applicability of MEMS sensor technology with noisy data for industry (robotics). The problem will be solved through the use of machine learning for non-linear automatic control systems and the development of new algorithms for reconstructing the robot's trajectory based on MEMS inertia sensor data.
The goal of the project is to develop algorithms for determining the position and spatial orientation of a mobile robot using MEMS-sensor data as a feedback signal. A distinctive feature of the project is the use of machine learning to solve the tasks of the robot navigation and automatic control.
Expected and achieved results of the project:
Year | The results obtained from the research. Publications (with links to them) and patents; information for potential users. |
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2023 |
A comparative analysis of the advantages and disadvantages of modern approaches to the control and navigation of mobile robots will be carried out. |
2024 |
Two components of the computer simulation environment: a MEMS sensor data simulator installed on a mobile platform and a mobile platform simulator will be developed. |
2025 |
An experimental environment for full-scale experiments will be developed: an experimental mobile robot for testing new algorithms for navigation and automatic platform control will be designed and mounted. |
Infographic
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